Materials physics for materials design_The attractions of computor simulation ref. MIT's Michael Demkowicz Grp.

The attractions of computor simulation although mostly for resolution of complex multi-variable and multi-dimentional problems they are also an excellent tool for visulisation and highly attractive communication.

Here are some examples taken from MIT's  Demkowicz Group 

OVERVIEW OF THE DEMKOWICZ APPROACH:

Computational materials design using Reduced Order Mesoscale Models (ROMMs)

FIVE PROJECT EXAMPLES:

1. Mitigating hydrogen- and helium- induced damage.

2. Radiation-resistant amorphous materials.
3. Materials design through interface engineering.
4. Bayesian inference applied to grain boundaries.
5. Prediction and prevention of wear.

 Mitigating hydrogen- and helium- induced damage

Although they may "seem benign", hydrogen (H) and helium (He) can both cause severe embrittlement in structural materials. H embrittlement is especially problematic in acidic environments, such as those encountered in deep oil wells, while He embrittlement may occur in nuclear reactors. By controlling how H and He atoms diffuse, cluster, and interact with crystal defects, we are designing new embrittlement-resistant materials for energy applications

NB. Hydrogen embrittlement is a well known phenomena and has long been documented. He damage came to the fore due to the extensive use of Ar and/or  He in powder metallurgy where one or other of these inert gases are used to atomise liquid metal streams from typically VIM-Vacuum Induction Furnaces.

 Radiation-resistant amorphous materials

Crystalline materials are tough, but susceptible to radiation damage. To create materials with significantly improved safety, performance, and reliability for advanced nuclear reactors, we are investigating the radiation response of amorphous (non-crystalline) materials. Combining both crystalline and amorphous solids into composites may lead to materials that capitalize on the strengths of both while compensating for their weaknesses.

  Materials design through interface engineering

Although they are sometimes viewed as no more than dividing surfaces between neighboring constituents, solid-state interfaces (most usually called grain boundaries) in fact have distinct physical properties of their own. We are using the properties of interfaces to design new materials with radically enhanced performance under extreme irradiation and mechanical loading.

  Bayesian inference applied to grain boundaries

Many materials are so complex, that we can only gain partial understanding of their structures and properties using individual experimental or modeling methods. However, we can gain a more complete picture by combining results from many kinds of different techniques. Bayesian inference provides a rigorous mathematical framework for intelligently combining vastly different types of data such that the whole is greater than the sum of the parts. We are applying this technique to infer the properties of grain boundaries as a function of their crystallographic character.

 Prediction and prevention of wear

Wear is a life-limiting materials degradation mechanism in many applications. For example, wear by grid-to-rod fretting (GTRF) is the most common cause of fuel leaks in current nuclear reactors. We are developing microscale simulations for modeling wear at the level of single asperities and debris particles. These simulations will lead to better predictions of wear and to the design of materials with improved wear resistance.

REFERENCES:

1. Projects.

2. People.

3.Materials physics for materials design _Slide show of magnified computor simulation images.

4. Biography & Selected Publications.

Materials design through interface engineering

Although they are sometimes viewed as no more than dividing surfaces between neighboring constituents, solid-state interfaces in fact have distinct physical properties of their own. We are using the properties of interfaces to design new materials with radically enhanced performance under extreme irradiation and mechanical loading.

Stainless steel optimization from quantum mechanical calculations_No getting away from a great material "Steel, nor from a great journal_Nature Materials

No getting away from Nature Materials -Hope to come back to this theme.

Stainless steel optimization from quantum mechanical calculations

Levente Vitos^1,2, Pavel A. Korzhavyi¹ & Börje Johansson^1,3

Abstract

Alloy steel design has always faced a central problem: designing for a specific property very rarely produces a simultaneous significant improvement in other properties^1, 2. For instance, it is difficult to design a material that combines high values of two of the most important mechanical characteristics of metals, hardness and ductility. Here we use the most recent quantum theories of random alloys³ to address a similar problem in the design of austenitic stainless steels, namely, to combine high mechanical characteristics with good resistance against localized corrosion. We show that an optimal combination of these basic properties can be achieved in alloys within the compositional range of commercial stainless steels. We predict, first, that Fe₅₈Cr₁₈Ni₂₄alloys possess an intermediate hardness combined with improved ductility and excellent corrosion resistance, and, second, that osmium and iridium alloying additions will further improve the basic properties of this outstanding class of alloy steels.

REFERENCE: Nature Materials 2, 25 - 28 (2003) 

Published online: 15 December 2002 | doi:10.1038/nmat790

Subject Categories (in Nature Materials nmat for short): Metals and alloys | Computation, modelling and theory